Holography is a very broad discipline. Since its inception in the late 1940s and its evolution in the 1960s and beyond, it has grown to become a well-researched field with many diverse applications. While there are many areas of holography, this article has focused on digital holography. The Roadmap paper is comprised of 25 sections contributed by prominent experts in the field to provide an overview of various aspects of digital holography. We start the roadmap article by presenting the origins of holography in Section2by J. W. Goodman. Then the author of each remaining section describes the progress, potential, vision, and challenges in a particular application of digital holography. A vast array of topics are covered including self-referencing digital holography, information security, lab-on-chip holography, tomographic microscopy with randomly structured illumination, automated disease identification by digital holography, label-free live cell imaging, digital holography with machine learning, disordered optics for digital holography, SLM-based incoherent digital holography, off-axis holographic spatial multiplexing, compressive sensing, single-pixel digital holography, holographic 3D reconstruction with multiple scattering models, machine-learning-enabled holographic near-eye displays for virtual and augmented reality, integration of light-field imaging and digital holography, and digital holography macro industrial applications and inspection. Table1has a list of all the sections and their corresponding author.
As in any overview paper of this nature, it is not possible to describe and represent all the possible applications, approaches, and activities in the broad field of digital holography. We apologize in advance if we have not included any relevant work in digital holography. Hopefully, the large number of cited references can aid the reader with those areas not fully discussed in this Roadmap.
Funding.National Research Foundation Singapore; Intelligence Advanced Research Projects Activity; Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (2021-0-00745); National Research Foundation of Korea (2015R1A3A2066550); Office of Naval Research
(N000141712405); Army Research Office; National Science Foundation (1839974); Ford Motor Company; Euro-pean Research Council (ERC StG 678316); National Science Foundation (1846784); National Science Foundation (1813848); Universitat Jaume I (UJIB2018-68); Generalitat Valenciana (PROMETEO/2020/029); Agencia Estatal de Investigación 110927RB-I00/AEI/10.13039/501100011033); Agencia Estatal de Investigación (PID2019-104268GB-C22/AEI/10.13039/501100011033); Generalitat Valenciana (PROMETEO/2019/048); Ministerio de Ciencia, Innovacion y Universidades (RTI2018-099041-B-I00); Israel Science Foundation (1669/16); NSF PATHS-UP; Canada Excellence Research Chairs, Government of Canada; Canada Foundation for Innovation (342, 36689); Natural Sciences and Engineering Research Council of Canada (RGPIN-2018-06198); European Commission (H2020-ICT-2016-1 MOON Grant 732969); Austrian National Science Foundation (FWF grant no. P 29093-N36); Department of Science and Technology India (IDP/MED/34/2016); Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund (TEAM TECH/2016-1/4); Horizon 2020 Framework Programme (101016726);
Morphological Biomarkers for early diagnosis in Oncology (MORFEO) (MUR- PRIN 2017 Prot. 2017N7R2CJ); Hong Kong Polytechnic University (4-ZZLF, 1-W167); Board of Research in Nuclear Sciences (2013/34/11/BRNS/504);
Science and Engineering Research Board (EMR/20l7/002724).
Disclosures.Pierre Marquet declares a potential conflict as co-founder of Lyncée Tec. Rainer A. Leitgeb authors patents with Carl Zeiss Meditec. The rest of the authors declare no conflicts of interest.
Data availability.Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
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